by A new study published in Nature reveals that artificial intelligence (AI) technology can significantly speed up the identification of brain tumor types during surgery, providing neurosurgeons with the information they need to adjust their surgical strategies on the spot. This groundbreaking technology, developed by researchers from UMC Utrecht, the Princess Máxima Center for pediatric oncology, and Amsterdam UMC, allows for accurate tumor type identification within 1.5 hours, a process that would typically take up to a week.
Surgery is often the first step in treating brain tumors, but neurosurgeons usually lack precise knowledge of the tumor type and its aggressiveness during the procedure. The exact diagnosis is typically available only after surgery, once the tumor tissue has undergone visual and molecular analysis by a pathologist. However, the new deep-learning algorithm developed by UMC Utrecht is capable of learning from millions of simulated DNA snapshots, enabling the identification of tumor types within 20 to 40 minutes. This breakthrough allows neurosurgeons to adjust their surgical strategies immediately, if necessary.
Jeroen de Ridder, a research group leader within UMC Utrecht and Oncode Institute, explains that the algorithm was developed using the latest advancements in computer science and deep learning, allowing it to analyze complex molecular datasets obtained from tumor tissue samples. The algorithm was trained and tested using a comprehensive biobank maintained by the Princess Máxima Center, which stores tissue samples from children with brain tumors.
The effectiveness of the new technology was demonstrated through multiple brain surgeries performed on both adult and pediatric patients. The total duration of the procedure, from the collection of tissue in the operating room to the determination of tumor type, ranged from 60 to 90 minutes. The Princess Máxima Center has already begun utilizing the technique with children, as the results were deemed reliable enough to potentially impact surgical strategies. Amsterdam UMC also plans to incorporate the technology into daily practice to expedite diagnosis.
Eelco Hoving, a pediatric neurosurgeon and clinical director of neuro-oncology at the Máxima Center, emphasizes the significance of DNA analysis during surgery. By knowing the tumor type during the initial surgery, surgeons can avoid the risks and stress associated with a second surgery to remove remaining tumor tissue. This groundbreaking technology has the potential to optimize the outcome of brain tumor surgeries and improve patients’ quality of life.
While the new technique has shown promising results, further research is necessary to expand its applications. The algorithm needs to be trained on more tumor types to meet international standards for data comparison. Additionally, the outcomes of the new technology will be compared to the traditional method in collaboration with other national and international centers to assess its impact on long-term patient outcomes. Nevertheless, the study represents a significant step forward in leveraging AI technology to expedite and improve brain tumor diagnosis during surgery.
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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
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